Effects of Pre- and Post-Processing on type-based Embeddings in Lexical Semantic Change Detection

Code

• github.com/Garrafao/LSCDetection
  OfficialIn papernone★ 31

Abstract

Lexical semantic change detection is a new and innovative research field. The optimal fine-tuning of models including pre- and post-processing is largely unclear. We optimize existing models by (i) pre-training on large corpora and refining on diachronic target corpora tackling the notorious small data problem, and (ii) applying post-processing transformations that have been shown to improve performance on synchronic tasks. Our results provide a guide for the application and optimization of lexical semantic change detection models across various learning scenarios.

Tasks

Reproductions